Acceptance of CRM-systems

Figure 27 shows the distribution of the main influencing factors for the acceptance of CRM-systems. A certain similar distribution of the determinants (person, technology, and management) can be recognized. Task-related and organizational factors account for the least amount. This means that the acceptance of CRM-systems in the packaging industry largely depends on person-related, technology-related, and management-related factors.

Figure 27: Analysis of main determinants for acceptance

Source: Author’s figure

In a further step it has been examined into which sub categories the result of the distribution of the main determinants can be classified. The selection of sub categories was based on the sub categories of the determinants of acceptance of CRM-systems, described in the theoretical part of this thesis.

Figure 28 is indicating that the system’s supportability has the biggest impact on acceptance with a level of 16%. During the interviews, the added value has been often mentioned in this relation. Only the recognition of the meaningfulness of a system and the provision of an added value for the daily work can lead to acceptance by the respective users.

The employees must be convinced that the CRM-system is important in terms of their daily work and their success as sales representatives. Since some people might be not open-minded

enough with regards to changes, they must be convinced that the respective change brings added value to them (change management). Then acceptance can take place. User-friendliness plays a decisive role. The system’s utilization rate will be correspondingly low, if this is not the case.

Figure 28: Analysis of sub categories

Source: Author’s figure

The analysis also showed that an organizational culture that supports and is open to innovative technologies is important (12%). The willingness to innovate should therefore be correspondingly high and knowledge must be shared. The data input must be simple and accessible from anywhere. The system must not be used as a control function and should provide an actual benefit. There must be training during the implementation and installation phase of a CRM-system. Furthermore, regular training on a CRM-system is important, as the system is dependent on the quality of the data and the better the employees are trained, the better the input and quality of the data. The advantages of such a system need to be illustrated by clear and understandable examples.

The importance of the CRM-system must be clarified throughout the organization starting from the management level (sub categories “planning” and “leadership”). There must be a willingness of the organization to work with the CRM-system in the future. All users should be informed about the meaningfulness and importance for the corporation. Starting from an expectation, the necessary decisions must be taken. The use of a CRM-system may not exceed

a certain amount of work, since otherwise it loses its benefit. It must ensure that employees have enough time for other work. Such a system is intended to simplify work for users. CRM-approaches from the past have failed due to lack of acceptance and too high complexity.

Systems are regarded as control instruments, which are associated with additional work.

As part of the generalization of the text passages and evaluation of the conducted interviews, the following criteria for the acceptance of CRM-systems in the packaging industry could have been identified.

 Added value

 Awareness creation

 Management, commitment, and involvement

 Planning and implementation

 Usability

For the acceptance of a CRM-system, the added value is crucial. The user must realize that the system is more than just a management control tool. They need to feel that the use of the system gives them additional value. The usability, as a technology-related determinant of the acceptance of CRM-systems, describes that CRM-systems must be easy, fast, and mobile with regards to their usage. The system must support the user in everyday life and should be logical and intuitive, as complex systems lead to rejection and demotivation. The awareness that the CRM-system is important to the company is part of the organizational culture. The system must therefore be transparent and not giving the user the feeling of being replaceable.

There must be a rethink, because nowadays, many leads cannot be handled alone. CRM must be understood as part of the corporate strategy.

As part of the planning and implementing of a CRM-system, management must make fundamental decisions about goals, usage, and expectations. Employees must be involved in the process right from the start. The decision for a CRM-system is made by the top management.

The management must therefore stand behind the project and support it. Employees who are not convinced by the system must be motivated accordingly by them.

During the empirical investigation it could be determined that certain influencing factors are responsible for the acceptance of CRM-systems. The qualitative evaluation of the interviews led to the development of a collection of criteria to promote the acceptance of CRM-systems in

the packaging industry. These categories must be considered so that the system can be accepted by the employees or users.

4.2 Quantitative research

4.2.1 Execution

The following hypotheses were developed based on the interviews that were carried out, analysed, and explained in the previous chapter 4.1.

H10 There is no connection between the age of a sales representative and the characteristic

“customizability” that a CRM-system should have.

H11 There is a connection between the age of a sales representative and the characteristic

“customizability” that a CRM-system should have.

H20 There is no correlation between the age of a sales representative and the "extra work"

concern about a CRM-system.

H21 There is a correlation between the age of a sales representative and the “extra work”

concern about a CRM-system.

H30 There is no connection between previous experience in dealing with CRM-systems and the concern “technical overload” compared to CRM-systems.

H31 There is a connection between previous experience in dealing with CRM-systems and the concern “technical overload” compared to CRM-systems.

The link to the online questionnaire was sent to 120 people. A total of 101 people from various Constantia Flexibles locations took part in the survey. The response rate is thus 84.16%.

The people surveyed all come from different sales departments. As can be seen in figure 29, 44% of the salespeople surveyed are masculine and 56% of the informants are feminine.

Figure 29: Division of gender

Source: Author’s figure

4.2.2 Results

The outcome of the quantitative survey is described in this chapter. Figure 30 shows how many of the people surveyed are in which age groups. 33 of the respondents are 30 years or younger. There are 28 people each between the ages of 31 and 40 and between the ages of 41 and 50. The rest of the people are over 51 years old. The mean age of the informants is 37.6 years.

Figure 30: Age groups of respondents

Source: Author’s figure

In addition, the highest level of education completed by the respondents was asked and visualized in figure 31. Four people have completed an apprenticeship. None of the respondents have completed compulsory schooling or a technical college. Most people have completed a master’s/diploma degree at a university or university of applied sciences. The completion of a bachelor's degree at a university or technical college or the degree with a Matura are in the middle.

Figure 31: Highest completed education

Source: Author’s figure

The first question in the questionnaire, as visualized in figure 32, relates to information on how the respondents rate their experience with CRM-systems. Since a CRM-system at Constantia Flexibles was only recently implemented or is currently in the implementation phase, only 3% of those questioned said they had very good experience in dealing with CRM-systems. 33% rated their experience as good and another 39% have mediocre experience in dealing with CRM-systems.

Figure 32: Experience with CRM-systems

Source: Author’s figure

For the second question, "How important are the following properties that a CRM-system should have?", the most important properties were completeness, reliability, usefulness, and timeliness. As can be seen in figure 33, the format was least often defined as “very important”

for the respondents.

Figure 33: Importance of CRM-properties

Source: Author’s figure

The third question answered the importance of various activities that a CRM-system should have and has been visualized in figure 34. Faster data and knowledge exchange are the

most important activity of a CRM-system for the people surveyed. More efficient customer service and access to customer data were named as further important activities. This was followed immediately by support for the sales processes and improved opportunity and lead management. Protection against data loss and misuse and transparency in customer care were often described as less important.

Figure 34: Importance of CRM-activities

Source: Author’s figure

Figure 35: Concerns about using a CRM-system

Source: Author’s figure

Figure 35 shows how strongly the following concerns affect employees when using CRM-systems. Overtime has a strong influence on over 70% of those surveyed when using it.

Restrictions on freedom of work and changes in working methods come in second and third

place. Higher performance pressure and poor usability were also cited as strong concerns of the sales staff. Loss of status and excessive technical demands have the least influence on the sales employees surveyed.

Figure 36: Frequency of use of CRM-systems

Source: Author’s figure

Figure 36 shows the frequency of use after the implementation of a CRM-system in the corporation. 76% of the people surveyed think that they will use the CRM-system every day after successful implementation and only 2% assume that they will rarely use it.

The hypotheses testing is now carried out, starting with the correlation test between age and properties in relation to CRM-systems. As it can be seen in table 7, p is 0.001 < 0.05 (the significance is less than alpha). It can thus be said that there is a connection between the age of a sales employee and the property “customizability” that a CRM-system should have.

Therefore, hypothesis H11 is accepted.

H11 There is a connection between the age of a sales representative and the characteristic

“customizability” that a CRM-system should have.

Table 7: Correlation test between age and properties in relation to CRM-systems

Related variables Chi square, Pearson

Asymptotic significance Spearman

Age and reliability 0.204  not significant -0.289  no correlation

Age and controllability 0.139  not significant 0.183  medium to strong correlation

Age and customizability 0.001  highly significant* 0.417  strong correlation

Age and usefulness 0.073  only 27% significant -0.280  no correlation

Age and simplicity 0.049  51% significant 0.202  strong correlation

Age and actuality 0.035  65% significant -0.302  no correlation

Age and format 0.151  not significant 0.190  medium to strong correlation

Age and flexibility 0.419  not significant 0.060  little correlation

Age and accessibility 0.363  not significant -0.238  no correlation

Age and quality of information 0.358  not significant -0.088  no correlation

Age and completeness 0.046  54% significant -0.152  no correlation

*99% probability that there is a connection

Source: Author’s table

The correlation testing between experiences and concerns about CRM-systems is shown in table 8. p = 0.100 > 0.05 shows that the significance is greater than alpha. It can therefore be said that there is no connection between the age of a sales representative and the concern about

“extra work” in relation to a CRM-system. Therefore, the hypothesis H20 is accepted.

H20 There is no correlation between the age of a sales representative and the "extra work"

concern about a CRM-system.

Table 8: Correlation test between age and concerns about extra work

Related variables Chi square, Pearson

Asymptotic significance Spearman

Age and overtime 0.100  not significant -0.289  no correlation

Age and transparency/control 0.222  not significant -0.387  medium to strong correlation

Age and status loss 0.009  highly significant* -0.130  no correlation

Age and technical overload 0.006  highly significant** -0.149  no correlation

Age and working style change 0.000  highly significant -0.390  no correlation Age and higher susceptibility to

errors 0.081  only 19% significant -0.059  no correlation Age and performance pressure 0.000  highly significant -0.468  no correlation Age and restriction of freedom

of work 0.116  not significant -0.278  no correlation Age and poor usability 0.271  not significant -0.151  no correlation

*91% probability that there is a connection

**94% probability that there is a connection

Source: Author’s table

The correlation testing between experiences and concerns about CRM-systems is shown in table 9. p = 0.035 < 0.05 shows that the significance is less than alpha. It can thus be said that there is a connection between the experience of a sales employee in dealing with CRM-systems and the concern that a CRM-system is “technically overwhelmed”. Therefore, hypothesis H31 is accepted.

H31 There is a connection between previous experience in dealing with CRM-systems and the concern “technical overload” compared to CRM-systems.

Table 9: Correlation test between experience and concerns

Related variables Chi square, Pearson

Asymptotic significance Spearman

Experience and extra work 0.413  not significant -0.050  no correlation Experience and transparency

and control 0.222  not significant 0.144  medium to strong correlation Experience and loss of status 0.001  highly significant* 0.319  strong correlation

Experience and technical

overload 0.035  65% significant -0.267  no correlation Experience and change in

working method 0.157  not significant -0.289  no correlation Experience and higher

susceptibility to errors 0.000  highly significant -0.363  no correlation Experience and pressure to

perform 0.001  highly significant* -0.030  no correlation Experience and restriction in

freedom of work 0.057  43% significant -0.120  no correlation Experience and poor usability 0.939  not significant -0.014  no correlation

*99% probability that there is a connection

Source: Author’s table

In document DOCTORAL (Ph.D.) DISSERTATION (Pldal 109-121)